blsm: The Bipartite Latent Space Model

In selenashuowang/jlsm: Joint Latent Space Model for Social Networks with Multivariate Attributes

Description

Function to fit the bipartite latent space model (BLSM) outlined in Wang et al. (2021)

Usage

blsm(Niter, Y.ia, D)

Arguments

Niter	number of iterations
Y.ia	N by M matrix containing the binary multivariate attributes
D	number of dimensions in the data

Value

list containing:

• lsmhEZ.i (N x D) matrix containing the posterior means of the latent person positions

• lsmhEZ.a (M x D) matrix containing the posterior means of the latent item positions

• lsmhVZ.0 (D x D) matrix containing the posterior variance of the latent person positions

• lsmhVZ.1 (D x D) matrix containing the posterior variance of the latent item positions

• lsmhAlpha.1 scaler of mean of the posterior distributions of α.1

• lsmhKL expected log-likelihood

Examples

attach(french)
a=blsm(Niter=10,Y.ia,D=2)

selenashuowang/jlsm documentation built on Feb. 20, 2021, 6:39 a.m.